In 1995
the Florida Department of Education and the Florida Solar Energy
Center jointly sponsored a test of occupancy sensors used to control
lighting in a Florida school. Occupancy sensors replace conventional
light switches and use passive infrared or ultrasonic sensing to
control lighting in classroom and other spaces. The test was intended
to demonstrate the performance of such controls in saving energy
in Florida educational facilities.

The evaluation
was performed at Northwest Elementary School in Pasco County on
Florida's west central coast. A before and after monitoring protocol
was utilized for the study which saw lighting circuits for 33 classrooms
and seven offices sub-metered. Fifteen minute electrical demand
data were taken for six months prior to the lighting controls being
modified to accomodate occupancy sensors. Recorded data in the baseline
period showed that lighting made up approximately 24% of total electrical
energy use at the school.

The test
building was unusual in that the it contained a modern efficient
lighting system with T8 flourescent lamps and electronic ballasts.
More importantly, the Pasco County features one of the most aggresive
energy management programs of any district school board in the state.
Even before installation of the occupancy senors, lighting was effectively
controlled by facility staff so as to prevent waste. Given these
factors, it was expected that the evaluation in Northwest Elementary
would provide insight into the minimum savings that could
be expected from the technology in Florida school.

A total
of 46 occupancy sensors were installed in August, 1995 and then
carefully adjusted in terms of location, time delay and sensing
sensitivity over the following two weeks. Data were taken in a post
retrofit configuration for five months. The analysis of the comparative
pre and post retrofit periods showed that the occupancy sensors
saved an average of 10% of the pre-retrofit lighting energy (97
kWh/Day) with greater reductions to total energy due to reduced
load on the air conditioning system. Most of the savings occurred
during the evening hours so that monthly peak electrical demand
was little affected.

Including
costs of installation and commissioning, the payback of the occupancy
sensor retrofit was five years with a 21% simple rate of return
from the investment. This performance is considered excellent given
the fact that the building already had an efficient lighting system
which was responsibly controlled prior to the occupancy sensor installation.
The project results indicate that with proper installation and adjustment
(which was found to be critically important to user acceptance)
occupancy sensor technology will provide economically attractive
returns either in new or existing Florida educational facilities.

I.
Introduction

In 1993,
the Florida Department of Education (FDOE) and the Florida Solar
Energy Center (FSEC) began an energy efficiency campaign for Florida's
schools. FDOE funded FSEC to produce a comprehensive analysis of
energy efficiency options for new educational facilities.
The findings of the study were compiled in a training manual and
presented at three workshops in the Spring of 1995. However, during
the presentations of the research findings to the Florida Educational
Facilities Planners Association (FEFPA) many attendees requested
information on the performance and economics of retrofit energy
efficiency measures. Furthermore, a number of energy-efficiency
technologies were identified whose savings were difficult to quantify.
FDOE and FSEC then planned to meet this need by staging a series
of research-demonstration projects to quantify performance in operating
schools.

For the
first technology demonstration, FSEC chose to study occupancy sensors,
primarily because little performance data were available for this
technology. Occupancy sensors replace standard light switches and
turn off classroom lighting when students and teachers vacate spaces
for a given period of time. Since savings are heavily influenced
by occupants and their behavior, laboratory studies are impossible.

A Pasco
County school, Northwest Elementary, was selected for the project
in the Fall of 1994. The study was intended to provide information
to measure the effectiveness of occupancy sensors in reducing two
loads:

Lighting
energy consumption, and

Total
energy consumption

Instrumentation
was installed and data collection began in February of 1995. Data
in the pre-retrofit baseline condition was collected up through
August 7, 1995. The experiment was concluded in December of 1995
after a post retrofit monitoring period was completed. The results
of the study will be presented to the educational facilities design
community in its 1996 meetings.
II.
Lighting Energy Use in Florida Schools

Electricity
for interior lighting systems makes up about a third of the energy
used in Florida schools as seen in Figure
1. Further, intenal heat produced by interior lighting contributes
about 23% of the peak sensible air conditioning load as shown
in Figure 2. Thus, lighting consumption indirectly increases facility
energy demand by adding to the space cooling loads.

Figure 1. Energy end uses in Florida schools.

Figure 2. Components of the peak HVAC load in typical new educational
facilities predicted by the hourly simulation DOE2.1D

School
have two primary options for reducing the lighting energy load:

Increase
the efficiency of the lighting system, or

Reduce
the operating hours of the system
One strategy employs more efficient lamps, ballasts, and fixtures
to reduce the energy required to provide the desired level of work
place illuminance. The second method employs lighting controls to
reduce the amount of time the system is powered. Conventional controls
include time clocks that turn lights off after hours and master
switches which use "sweep control" to turn off a zone
or building. Occupancy sensors match the electrical lighting to
the space conditions based on space use.

While
more efficient systems, such as T8 lamps with electronic ballasts,
have repeatedly produced significant savings, objective data on
the energy reduction from occupancy sensors are more elusive. Savings
critically depend on how occupants use a space. Therefore, savings
for schools hinge on a critical question: How often and how long
are school spaces currently unoccupied with the lights unintentionally
left on? III.
Background

The research
team's decision to study occupancy sensors was based on the interest
expressed by Florida's school design community during the May 1995
workshop series. More debate surrounded occupancy sensors than any
of the energy conservation measures (ECMs) presented. Discussion
elicited three fundamental issues:

Product
quality

Cost/benefit

Reliability.

As an
inexpensive option and potential retrofit measure, occupancy sensors
appeal to the school building industry. On the other hand, problems
with early installations have damaged the reputation of the technology
for some users (Energy User News, 1991).(1) The
devices themselves are of two primary types: passive infrared and
ultrasonic as described in Appendix A. Reports suggested that older
products failed regularly or turned off lights on occupied classrooms,
requiring extra maintenance and/or causing frustration for school
personnel. While many reported these type of problems, others expressed
a positive opinion of occupancy sensors. These reports typically
came from persons with more recent experience, suggesting that the
reliability of the technology had improved.

Even
those workshop attendees who viewed the sensors positively, however,
reported problems with performance. These problems include "false
positives" and "false negatives"; triggering the
lights on or off at inappropriate times. It was hoped that FSEC's
assessment would provide objective performance data on occupancy
sensors for Florida's school design and management community and
help resolve these questions.

Some
educational facilities planners questioned the economics of occupancy
sensors. They argued that classrooms, which make up the bulk of
primary and secondary school facilities, do not remain unoccupied
for long periods and that most teachers diligently turn lights off
upon leaving rooms. Many expressed the opinion that occupancy sensors
would be most appropriate for intermittently used spaces, such as
break and copy rooms. However, without empirical evidence, the performance
and economics of the technology remain the subject of speculation.

Generally,
lighting energy reductions from occupancy sensors will roughly follow
room vacancy rates. Savings will be, of course, modified by occupant
responsiveness in turning off lights in unoccupied areas. Measured
lighting energy savings from occupancy sensor installations are
surprisingly sparse. Both the Electric Power Research Institute
and ASHRAE estimates an average 30% savings from this technology
in generic assessments for commercial buildings (EPRI, 1993; ASHRAE,
1989). These data are generally supported by a utility evaluation
performed by Consolidated Edision which found a 30% reduction in
average lighting demand for its projects which installed occupancy
sensors (Audin, 1993).

Measured
data from case studies also indicates good performance from occupancy
sensor installations. A retrofit of an office building with passive
infrared occupancy sensor controls in South Australia yielded a
40% reduction in lighting energy use with a simple payback of two
years (Caddet, 1995). Also, several case studies of occupancy sensor
installations show savings of 25 - 75% in variety of spaces (EPRI,
1994). The Florida Solar Energy Center has conducted two previous
occupancy sensor studies. One studied savings for facility restrooms,
while the other studied a small office building. Savings in the
restrooms exceeded expectations at greater than 60% while the average
savings in a small office building were approximately 15% (BDAC
Energy Files, 1995). The reductions were manifested primarily during
the lunch hour and after hours. Finally, a detailed study of occupancy
sensors used in a national laboratory found a 31% average lighting
energy reduction (Richman, et al., 1995) with savings strongly affected
both by space type and time delay setting. Performance data specific
to educational facilities is more limited. Occupancy sensor manufacturers
often claim a 40 - 50% savings in classroom energy use (Novitas,
1993, Watt-stopper, 1994). A pertinent case study at the University
of New Hampshire showed a reduction in classroom lighting system
on-time of some 3 hours per day (EPRI, 1994). However, prior to
this study no evaluation had examined the savings in a Florida classroom
environment, and no information existed on possible impacts on monthly
demand.
IV.
Site Description and Monitoring Plan

Representatives
from the District School Board of Pasco County School approached
FSEC at the Summer 1994 meeting of the Florida Educational Facilities
Planners. The school's representatives expressed interest in participating
in a field study. Pasco County's Energy Management division funds
energy retrofits out of a revolving fund initiated by the school
board and probably represents the most progressive of such programs
in the state.

Northwest
Elementary school, on Florida's west coast near Hudson, was chosen
for the demonstration. The school facility is comprised of one main
building, a kindergarten annex, and several portable classroom units.
The 58,000 ft2 main building, which received the occupancy
sensor installation includes 33 classrooms, seven offices and
a cafeteria. The main building is shown as Figure 3; one of the
wall mounted occupancy sensors is seen in Figure
4.

Figure 3. Exterior of Northwest Elementary School
in Pasco County, Florida. The school was the site of an energy
saving technology demonstration by the Florida Department
of Education. The test was to determine if occupancy sensors
can save lighting energy.

Figure 4. FSEC engineer demonstrates the operation of wall
mount occupancy sensor. Some 46 sensors were installed at the school
for the test project. Each electronically detects the motion of students
and teachers through infrared-sensing and automatically turns off
lights when no motion is detected over a given period of time.

There
are some 200 school days per year, not including holidays, weekends
and summer recess. The school day extends from 7:00 AM - 3:45 PM,
although office and janitorial activities often extend beyond the
formal school day schedule.

The occupancy
sensors and monitoring equipment were obtained by FSEC and the installation
labor were provided by Withlacoochee River Electric Cooperative.
FSEC technicians audited the school on December 21, 1994 and subsequently
drew up a plan for instrumentation to monitor its energy use. A
survey of the school's electrical system revealed eleven circuits
of HVAC, five lighting circuits, two circuits of portable classrooms
and two circuits supplying a kindergarten addition. Occupancy sensors
emerged as the choice for improved lighting efficiency at the school
as it has few windows, but a modern efficient lighting system. A
combination of two lamp T10/magnetic ballast and T8/electronic ballast
fixtures illuminate each space.

The audit
team found that monitoring the portables and the kindergarten suite
was not feasible since separating the lighting load for these spaces
was cost prohibitive. The main building, comprised of classroom
pods, administrative spaces, a media center, and a cafeteria, became
the subject of the study. After reviewing the audit details, an
equipment list was established and the following metering equipment
was obtained.

Table
1Installed Metering Equipment

Project
Monitoring Equipment

Cost

Instrumentation

CR10
Multi-channel Datalogger

$
1,000

SW8A
Switch Closure Board

$
150

Modem/Power
Supply

$
100

Enclosure

$
200

Miscellaneous

$
300

Subtotal

$1,750

Transducers

100
amp, 3 phase

$
500

100
amp, 3 phase

$
500

100
amp, 3 phase

$
500

100
amp, 3 phase

$
500

100
amp, 3 phase

$
500

100
amp, 3 phase

$
500

50
amp, 1 phase

$
325

50
amp, 1 phase

$
325

Subtotal

$
3,150

Total

$
4,900

The Energy Manager for the school district, agreed to provide
a pulse count meter to measure total electrical consumption and
a dedicated telephone line for daily retrieval of the monitored
data. All equipment was then obtained, configured and calibrated.

V.
Instrumentation

FSEC
instrumented the facility on February 25, 1995 as shown in Figures
5 and 6. The data acquisition system measures various parameters
to assess the savings associated with the retrofit. Monitored meteorological
conditions were limited to ambient air temperature because the retrofit
would not likely be affected by weather conditions. Table 2 lists
the monitored parameters and the associated engineering units.

Figure 5. FSEC engineer, John Sherwin, installs an electric
power transducer as part of the instrumentation at Northwest
Elementary School on February 25, 1994.

Temperature
measurements were obtained using type-T thermocouples. A vented
enclosure shielded the ambient air temperature sensor from solar
radiation. Ohio Semitronics Watt-hour transducers with split
core current transformers measured lighting electricity use and
are accurate to with 2% of their full-range wattage (RMS).

Analog
and pulse outputs from the instrumentation were converted to digital
format and stored using a Campbell Scientific model CR10 datalogger.
Measurements are made at 0.2 Hz and averaged and stored every 15
minutes. Electrical power was totaled over 15 minute intervals.
Data were transferred from the datalogger via telephone modem to
FSEC's VAX 4000 nightly. Once processed and archived, the
daily data for the school were automatically plotted.

Plots
were inspected each morning by an FSEC project engineer to ensure
reliable data collection and proper metering. Lighting energy
is lowered by a reduction of lighting hours, while total energy is
conserved by reduction of direct lighting energy as well as heat
produced by lights as a component of the heating, ventilation,
and air conditioning (HVAC) load. These two parameters, total power
and lighting power, appear on FSEC's daily graphs of measured
data. An example of the daily data, for December 1st, 1995 is shown
in Figure 7.

Figure 7. Plot of total lighting power energy demand on Friday,
December 1, 1995.

FSEC
subtracted the energy use of the excluded kindergarten suite and
portable classrooms from the total power to obtain the energy use
of the main building:

Figure 6. Lighting electrical panel from which measurements
were taken. Split core current transducers
were fitted around the appropriate legs to measure lighting power
in the main building.

The
retrofit was scheduled for August 1995 to allow a roof repair and modifications
to pod classrooms in the early summer, but to secure the retrofit by
the start of the 1995-1996 school year.

VI.
Occupancy Sensor Installation

A total
of 46 passive infrared (PIR) occupancy sensors were installed
at Northwest Elementary from August 7, 1995 to August 15, 1995. The
installation was performed by a team of two electricians, a Research
Engineer from the Florida Solar Energy Center and the Energy
Coordinator from Pasco County. Approximately 33 classrooms, seven
offices, and a cafeteria were equipped with occupancy sensors, as
shown in Figure 8. Several offices had the wall switches replaced
with automatic wall switches. The remainder of the spaces (classrooms,
cafeteria, and larger offices) received ceiling mounted sensors.
The broad coverage of the ceiling mounted sensor minimized the need
for multiple occupancy sensors in all but five areas. The classroom
lighting layout and occupancy sensor installation and placement is
illustrated in Figures
9 and 10.

Figure 8. Floor plan of main building at Northwest Elementary
School in Pasco County indicating location of occupancy sensors.

Figure 9. Interior layout of lighting system in a typical
classroom at Northwest Elementary. The lighting fixtures consist
of four T-8 fluorescent lamps with a electronic ballast in a white
troffer covered by an acrylic prismatic diffuser.

Figure 10. FSEC engineer David Floyd installs run-time
metering equipment inside a single classroom lighting fixture.
Note the ceiling mounted occupancy sensor, located so as to scan the
entire classroom for motion.

Manufacturer literature for the selected sensors is attached in
Appendix A with a brief description of occupancy sensor technology.
Several other resources exist describing appropriate application
of occupancy sensors and issues regarding their effective use
(RPI, 1992; Audin, 1993; EPRI, 1994).

Classroom
occupancy sensors were located in a corner near the teachers desk
to minimize false "offs" when only the teacher was in
the classroom. All occupancy sensors were set to a 12 minute time
delay, which has worked well in most situations. Shorter time delays
will increase savings, however, false "offs" may also
increase. Past installation experience has shown that unless
the occupancy sensors are properly located, aimed and tested
by experienced personnel, poor savings and occupant dissatisfaction
will result. Figures 11 and 12 show time delay
adjustment on one the ceiling-mounted occupancy sensors as well
as use of run time loggers to verify control performances.

Figure 11. Pasco County School Board Energy Coordinator, Mike
Woodall, assists with the time delay adjustment of one of the ceiling
mounted occupancy sensors. The project found that proper set-up of
the time delay and sensitivity of the controls was essential to acceptable
performance.

VII.
Data Analysis

Accurate
assessment of lighting savings must be performed when the occupancy
patterns vary the least from the pre and post periods. Since the
most regular occupancy patterns occur during school days, accurate
assessment of lighting savings can only be performed during this
time period. Although savings are not being evaluated for the entire
year, school days account for approximately 93% of the total yearly
lighting demand and therefore are a good indicator of yearly savings.
Average daily total electrical consumption and average daily lighting
consumption for the pre and post-retrofit monitoring period are
shown in Figure 13 for school days. The pre-retrofit period
extended from February 27, 1995 - June 9, 1995, comprising some
69 school days and 30 non-school days. The post retrofit period
began on September 5, 1995 and ended on December 8, 1995, comprising
84 school days and 28 non-school days.

Of the
total power demand during the pre-retrofit periods, 24.2% was used
for interior lighting. This is consistent with simulation predictions
for a school facility with a T8 lighting system (McIlvaine, et al,
1994). Lighting systems using older technology such as T12 lamps
and magnetic ballasts (which comprise the lighting systems in the
majority of Florida schools) would use a greater percentage of the
total for lighting power and would benefit more from the use of
occupancy sensors.

Upon
first examination of the lighting use plot in Figure
13, it is evident that prior to the installation of the occupancy
sensors there was little unintentional lighting during classroom
hours. A small dip in the post retrofit plot can be seen between
9:30 AM and 1:45 PM, when lights are manually turned off during
lunch. Also, when the school is vacated (when the night custodians
leave) from approximately 10 PM until the next morning, lights were
almost never left on. The diligent operation is due primarily to
the effective energy management program in Pasco County (Appendix
C). Thus, a fundamental point to be made regarding this study
is that the savings level from adding occupancy sensors is likely
to be as low as might be seen in almost any educational facility.
Other schools with typically less efficient lamps and less responsible
operation would experience considerably greater savings.

Figure 12. David Floyd checks the function of a time of use
lighting logger (small white box) which is installed inside the lighting
fixture. The lighting loggers were used to verify the proper performance
of the occupancy sensor controls during unoccupied periods.

Figure 13. Average total (left) and lighting (right) electricity
demand profiles measured at Northwest Elementary five months before
and after occupancy sensor retrofit.

The post
retrofit electrical demand lighting profile in Figure 13 shows the
additional savings produced by the occupancy sensors. Savings are
seen primarily after the school day ends, although there are some
reductions evident between lunch and 4:30 PM. Approximately 124
kWh are being saved each school day by the retrofit. This results
in a 10.2% savings (96.8 kWh/school day) in lighting, which is quite
substantial for a school that already practices good energy management.
Analysis of data on non school days is inconclusive since the occupancy
patterns changed between the pre and post periods. However, previous
research at FSEC suggests that if there are savings during non-school
days, they are small or possibly negative.

However
93% of the total power used during the year is on school days, and
therefore would not be influenced greatly by the non-school day
results. Using the lighting load savings between the pre and post
periods (96.8 kWh/school day) and assuming that there are 200 school
days per year the total lighting savings for the year is 19,360
kWh.

Since
lighting use also increases the load on the cooling system, a reduction
in lighting use would also lower the cooling load, especially in
central Florida where space cooling is the dominant end-use (approximately
90% of the year or 10.8 months). Total energy savings must also
include the reduction in the cooling load.

The economic
analysis will consider the lighting savings as well as the additional
savings from cooling load reduction. The resulting total yearly
energy savings of 26,620 kWh includes lighting (19,360 kWh) and
cooling (7,260 kWh).

Withlacoochee
River Electric Cooperative provides the power for Northwest
Elementary School. Their monthly utility rate is based on a fixed
consumer charge ($24.63), a demand charge ($6.16/kW), and a energy
charge ($.04765/kWh). Examination of the lighting demand profile
in Figure 13 shows no reduction in the average maximum demand
between the pre and post periods. Most of the savings occur during
the evening hours. Thus the only monetary savings will be due
to a reduction in energy (kWh). It is important to note, however,
that this is not always the case. When occupancy sensors are used
to control a building with a varying occupancy schedule, such
as a university, demand savings may be significant.

Using
the energy charge of $.04765/kWh the following savings were achieved:

The ratio
of the savings to cost results in a payback period of 4.8 years
and a simple rate of return of 21%. This is superior to the after-tax
revenues generated by almost any conventional investment and represents
a good use of discretionary funds.
IX.
Conclusions

Retrofit
of occupancy sensors in a Florida school showed a measured reduction
in lighting energy use of 10.2%. The economics were also attractive
with a 4.8 year payback and a 21% simple rate of return. The resulting
savings from this project are very promising considering that the
schools energy was already being managed quite well and the lighting
systems efficiency was already improved through ballast/lamp upgrades.

If the
schools lighting system was typical (magnetic ballasts with T12
lamps), it would be approximately 40% less efficient. Lighting savings
would increase to 27,104 kWh/year and cooling savings would increase
to 10,164 kWh/year. Under these circumstances the total monetary
savings would be $1,776 with a payback period of 3.4 years. If lights
are frequently left on after hours, the use of occupancy sensors
becomes even more attractive. We estimate that unintentional lighting
hours, and therefore saving, would be greater at most Florida educational
facilities.

Occupancy
sensors offer an accurate control method for lighting, if installed
and set up properly. They eliminate manual lighting control methods
(i.e. last one out turns the light off) and provide better savings
than time based control. Schools can benefit from this technology
if it is installed properly in appropriate areas. Appropriate areas
can easily be determined through the use of lighting loggers, and
other techniques such as random occupancy audits.
X.
Follow Up

Our findings
clearly showed an attractive economic performance of an occupancy
sensor retrofit in a Florida school which was already practicing
diligent energy management activities. However, to gauge typical
savings that might be experienced in Florida schools, we suggest
that the study be repeated in another more typical educational facility
with less stringent energy management activities. This would help
to better define average savings levels from this technology.
XI.
Acknowledgements

The Florida
Solar Energy Center would like to express its appreciation of the
Florida Department of Education in supporting this research. The
cooperation of the Pasco County School Board and the staff of the
Northwest Elementary School is also gratefully acknowledged. Finally,
the WattStopper Corporation provided a generous accommodation
for the purchase of the equipment in return for an objective third
party assessment.

Occupancy sensors, also called motion sensors, react to disturbance
in a space. They are designed to turn lights or other equipment on
when the space is occupied and off (after a specified time delay) when
the space is vacated. The most common load controlled is lighting;
however, more recently occupancy sensors can be designed to control
heating ventilating and air conditioning (HVAC), and office equipment
(monitors, printers, fans, etc.). The most common occupancy sensors
in use today use ultrasonic or infrared sensing techniques to detect
occupancy. Each technology has its advantages and disadvantages.

Ultrasonic (US) occupancy sensors emit inaudible sound waves that
bounce off objects in the room. It then measures the time it takes
for the sound wave to return. If there is any movement in the controlled
area the sound waves will return at a faster or slower rate, resulting
in a Doppler shift and occupancy detection. US sensors can detect motion
around corners. This makes them useful for spaces with large obstructions,
such as bath rooms. US sensors work best when movement is toward and
away from the sensor. The magnitude of required motion increases with
distance from the sensor.

Passive Infrared (PIR) sensors sense occupancy by "noticing"
the difference between a human body and the background. They accomplish
this by dividing the coverage area into zones. When a person passes
from one zone to another, the sensor detects occupancy. The better
sensors have more coverage zones. PIR sensors are a "line of
site" sensor and must have an unobstructed view of the entire
coverage area. PIR sensors work best when the movement is tangential
to the sensor. The magnitude of motion required to trigger the sensor
is directly proportional to the distance from the sensor.

One or both sensor types can be incorporated into a myriad of different
designs. The most common being automatic wall switches and ceiling
mounted sensors.

______________________

1. Each sensor costs
about $120 when purchased and installed in quantitiy.